Trends and Determinants of FDI with Implications of COVID-19 in BRICS

Foreign direct investment (FDI) movement to any country is recognized as an important criterion for economic strength and potentiality. Hence, the present study analyzes the motives of FDI inflows through the determinants and channels, namely horizontal or vertical FDIs and the impact of COVID-19 on FDI Inflows in BRICS countries during the period 1990–2020. The Kinked Exponential (deterministic) trend, and Zivot and Andrew’s trend equations are applied for the growth analysis of FDI inflows. Regarding the estimation of channels of FDI inflows in terms of horizontal, vertical, and hybrid motivations, dynamic panel data analysis using GMM for BRICS economies together and ARDL-PMG for individual countries is made. The findings show significantly positive growth in FDI inflows in all BRICS countries except India during the first decade of the present century. After that, these countries have experienced either significantly or insignificantly declining trends, except India, where the trend has significantly increased during this later period. From the overall analysis, we see that both horizontal and vertical motivations play a dominant role in determining FDI inflows for the BRICS countries. However, from country-wise estimations, it is observed that both horizontal and vertical motives are dominant factors for FDI inflows to India and Russia. In contrast, the horizontal motive of it is significant for China. For Brazil and South Africa, no motive behind FDI inflows appears significant. The pandemic situation significantly impacts attracting FDI in Brazil, while it remains insensitive in the rest of the BRICS countries. The findings reveal that FDI determinants are country-specific. So, the BRICS countries can design proper FDI policy and adopt more reforms in attracting FDI that may help improve their economic situation.

Estimating the Competitive Storage Model with Stochastic Trends in Commodity Prices

We propose a State-Space Model (SSM) for commodity prices that combines the competitive storage model with a stochastic trend. This approach fits into the economic rationality of storage decisions and adds to previous deterministic trend specifications of the storage model. For a Bayesian posterior analysis of the SSM, which is nonlinear in the latent states, we used a Markov chain Monte Carlo algorithm based on the particle marginal Metropolis–Hastings approach. An empirical application to four commodity markets showed that the stochastic trend SSM is favored over deterministic trend specifications. The stochastic trend SSM identifies structural parameters that differ from those for deterministic trend specifications. In particular, the estimated price elasticities of demand are typically larger under the stochastic trend SSM.

The Impact of Terms of Trade on the Export Structure of Manufactured Products in Different Economic Developing Status

The Prebisch-Singer Hypothesis states that in structural time series analysis, the terms of trade between primary products and manufacturers have a negative deterministic trend. Many researchers argued that the deterioration in trade is the type of country in which the products are exported, regardless of whether the types of products exported by such countries are primary or manufactured products. This paper employs a development-differentiated model to analyze the correlation between various terms of trade and the export proportion of manufactured products on different economies of development status. In the long run, stable co-integration relations exist between terms of trade and the export proportion of manufactured products for development status. Furthermore, the increased proportion of manufactured products exports is the Granger casualty for the worse terms of trade for several economies of development status. The results demonstrated that changing the terms of trade is significantly influenced by structured changes in the export proportion of manufactured products for the development status of economies.

Regional Investigation for Economies of Development Status on Changes in Export Structure of Deterioration Terms of Trade

The theory of Deterioration Terms of Trade states that the terms of trade between primary commodities and manufactures have a negative deterministic trend. However, the terms of trade for primary commodities have improved significantly because of higher prices of raw materials and natural resources due to the rapid development of some emerging developing countries. Literatures argued that the deterioration in terms of trade is the type of country in which the goods are exported rather than the types of goods exported by such countries are primary or manufactured goods. This paper employs regression models of alternative economies to analyze the correlation between terms of trade and manufactured goods export ratio. Results demonstrated that the Prebisch-Singer Hypothesis holds for all the economies except the developed ones, and the ITTs are worsened by increases in the proportion of manufactured goods for all the economies.

Using Hybrid Wavelet-Exponential Smoothing Approach for Streamflow Modeling

Considering the three intrinsic components (of autoregressive, seasonality, and error) of streamflow time series, the overall performance of the streamflow modeling tool is associated with the correct estimation of these components. In this study, a new hybrid method based on the wavelet transform (WT) as a multiresolution forecasting tool and exponential smoothing (ES) method, with two presented scenarios (WES1 and WES2), was introduced. To this end, the performance of the proposed method was investigated versus four conventional methods of the autoregressive integrated moving average (ARIMA), ES ad-hoc, artificial neural network (ANN), and wavelet-ANN (WANN) for daily and monthly streamflow modeling of West Nishnabotna and Trinity River watersheds with different hydro-geomorphological conditions. In the presented WES technique, firstly, WT is employed for decomposing the observed signal to one approximation (deterministic trend) and more diverse components of subseries (each at a specific frequency). Then, for the first scenario (WES1), only two subseries are introduced to the model as input parameters; however, for the second scenario (WES2), decomposed subseries are separately used as the inputs of ES models. The obtained results indicated that combining WT with the ES method and ANN led to more accurate modeling. The proposed methodology (WES2) that used all decomposed subseries separately improved the efficiency of models up to 30% and 10% for the daily dataset and up to 88% and 57% for the monthly dataset, respectively, for the West Nishnabotna and Trinity Rivers.

Estimating persistence for irregularly spaced historical data

This paper introduces to the literature on Economic History a measure of persistence which is particularly useful when the data are irregularly spaced. An illustration to ten historical unevenly spaced data series for Holland of 1738 to 1779 shows the merits of the methodology. It is found that the weight of slave-based contribution in that period has grown with a deterministic trend pattern.

NONLINEAR COINTEGRATING POWER FUNCTION REGRESSION WITH ENDOGENEITY

This paper develops an asymptotic theory for nonlinear cointegrating power function regression. The framework extends earlier work on the deterministic trend case and allows for both endogeneity and heteroskedasticity, which makes the models and inferential methods relevant to many empirical economic and financial applications, including predictive regression. A new test for linear cointegration against nonlinear departures is developed based on a simple linearized pseudo-model that is very convenient for practical implementation and has standard normal limit theory in the strictly exogenous regressor case. Accompanying the asymptotic theory of nonlinear regression, the paper establishes some new results on weak convergence to stochastic integrals that go beyond the usual semimartingale structure and considerably extend existing limit theory, complementing other recent findings on stochastic integral asymptotics. The paper also provides a general framework for extremum estimation limit theory that encompasses stochastically nonstationary time series and should be of wide applicability.

Prognóstico da série histórica do faturamento da indústria alimentícia brasileira utilizando técnicas de previsão

This paper’s objective is to verify which is the best forecasting technique, including the use of the forecasts’ combination to evaluate the prognosis of the Brazilian food industry’s revenues. The historical series of revenues has deterministic trend and seasonality. Thereby, the models chosen to work on were: SARIMA (3,0,0)×(0,1,1)12, SARIMA (4,0,0)×(2,0,0)12 and Holt-Winters Multiplicative. Analyzing the accuracy measures, to perform the series’ forecast it was used the combination of the three models, presented by the methods: Simple Arithmetic Mean, Ordinary Least Squares and Regression of Absolute Minimum Deviation. The results obtained by the forecast were satisfactory, showing that the Brazilian food industry’s revenues will have peaks of growth and decay in the next two years. Therefore, a preparation of the sector is necessary for the period in which a possible decrease in this revenue will occur, as well as dismissal of the workers, since it is the sector that most employs in Brazil.

A PROPERTY OF THE HODRICK–PRESCOTT FILTER AND ITS APPLICATION

This article explores a simple property of the Hodrick–Prescott (HP) filter: when the HP filter is applied to a series, the cyclical component is equal to the HP-filtered trend of the fourth difference of the series, except for the first and last two observations, for which different formulas are needed. We use this result to derive small sample results and asymptotic results for a fixed smoothing parameter. We first apply this property to analyze the consequences of a deterministic break. We find that the effect of a deterministic break on the cyclical component is asymptotically negligible for the points that are away from the break point, while for the points in the neighborhood of the break point, the effect is not negligible even asymptotically. Second, we apply this property to show that the cyclical component of the HP filter when applied to series that are integrated up to order 2 is weakly dependent, while the situation for series that are integrated up to order 3 or 4 is more subtle. Third, we characterize the behavior of the HP filter when applied to deterministic polynomial trends and show that in the middle of the sample, the cyclical component reduces the order of the polynomial by 4, while the end point behavior is different. Finally, we give a characterization of the HP filter when applied to an exponential deterministic trend, and this characterization shows that the filter is effectively incapable of dealing with a trend that increases this fast. Our results are compared with those of Phillips and Jin (2015, Business cycles, trend elimination, and the HP filter).